Companies commonly track assets by routinely performing inventory counts. This process often requires confirming that each recorded asset is correctly identified and stored in its correct location. In some scenarios, assets are stored in a room and the location recorded for the asset is a particular storage room. When storing assets at a room-level granularity, the inventory count process may be automated by tagging each asset with a radio-frequency identification (RFID) tag and confirming the asset is located in the correct room with an RFID reader. However, some companies may desire to track inventory at a shelf-level granularity. For example, for smaller components, inventory is stored on a rack that has multiple shelves, each shelf corresponding to a different shelf level. Moreover, storage racks may be deep and thus each storage location on the rack often has both a depth and shelf associated with it. Inventory counts are performed by confirming each asset is located on the correct rack, at the correct depth, and on the correct shelf-level. Shelf-level granularity requires identifying and confirming an XYZ location of an asset that corresponds to a rack, a rack shelf level, and a rack depth. Since traditional RFID solutions can only reliably identify whether an asset is inside a room, shelf-level inventory counts are typically performed manually and can take hours to complete. Therefore, a need exists to automate the tracking and inventory workflow of assets at a shelf-level granularity.